Advantages Of Web Scraping And Its Impact On The Digital World

Web Scraping is the process of extracting information and data from a website, transforming the information on a webpage into structured data for further analysis. Web scraping is also known as web harvesting or web data extraction.

With the overwhelming data available on the internet, web scraping has become an essential approach to learning about your business and using it to generate a dataset for input to your decision engine.

In this article, we are going to share some ideas regarding how real businesses are utilizing the advantages of web scraping and its processes to achieve their goals.

What Is Web Scraping?

The data displayed by most of the sites are viewed using web browsers. The web browser does not offer to save the data in a user-friendly format. The data can be saved only as a web page, and most web pages only give one option to the user- to manually copy and paste the data.

Web Scraping is a smart technique that can be utilized to extract vast amounts of information from the target websites. The extracted data then can be saved to a local file on your system or as a spreadsheet format. Web scraping advantages and processes can automate the processes of extracting data from the website using scripts.  

Where Can We Use Web Scraping?

Here are a few examples of how we have used web scraping in the past-

A ClassPass like company contacted us to build manual scraping processes for their gym website and wanted to update the gym schedule facility regularly. This would help users to get an idea about all gyms’ timing and events so they could decide to join the respective according to their comfort.

Through automated scraping service, we showed real-time schedules reflected on their website from as many as 100+ gyms immediately as they were updated on the respective gym’s website. We created an API/web service that could pick the schedules in real-time from gym websites. This API can be consumed by our backend node script that highlights schedules on the website.

The communication can be done over HTTP and in JSON format. It helped users to get gym-related information in a single click. By doing the automation we were able to reduce the turnaround time and decrease the number of manhours by 90%.

For an eCommerce company like, we built a data scraper to run a search for the product on the partner websites and check to see if the data is pulled from the right places and is put up accurately on the website.

A healthcare company had megabytes of data in excel sheets. We created a parser to parse the laboratory sample data for data validation purposes. The application we created applies the validation criteria & gives a warning on specific field data, based on the fields.

We worked with a subscription box company like Dollar Shave Club with over 100K monthly subscribers and helped them improve their bottom line by 5% by building a platform to better manage shipping timelines and routes so as to avoid damages and delays caused due to weather, all through the scrapping of different datasets and run predictive analysis on top of it.

Some Other Business Use Cases Of Web Scraping

Gathering data from multiple sources for

  • Market analysis and Lead generation
  • In-depth Research
  • Data Integration


  • Competitor’s inventory information
  • Stock prices
  • Order status from e-commerce portals
  • Opportunities
  • Automation of repetitive tasks
  • Procuring inventory
  • Getting product reviews

Meet Our Tech expert

Sandeep Natoo

Sandeep is a highly experienced Python Developer with 15+ years of work experience in developing heterogeneous systems in the IT sector. He is an expert in building integrated web applications using Java and Python. With a background in data analytics. Sandeep has a knack for translating complex datasets into meaningful insights, and his passion lies in interpreting the data and providing a valuable prediction with a good eye for detail.

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Advantages Of Web Scraping Solutions

To endure the success of your business/service, you must act fast and compete in the market. Web Scraping plays a pivotal role in the process of achieving success and developing the business. The Web scraping advantages and processes are as follows:

Save Cost

Web Scraping saves cost and time as it reduces the time involved in the data extraction task. These tools once created can be put on automation and hence, there is less dependency on the human workforce.

Accuracy Of Results

Web Scraping beats human data collection hands down. With automated scraping, you get fast and reliable results that can’t be humanly possible.

Time To Market Advantage

Accurate results help businesses save time, money, and human labor. This leads to an apparent time-to-market advantage over the competitors.

High Quality

Web Scraping provides access to clean, well-structured, and high-quality data through scraping APIs so that fresh new data can be integrated into the systems.

Our Step-By-Step Data Scraping Process For An eBay Like Ecommerce Platform

import re

import scrapy

class Ebay_Apparel(scrapy.Spider):

    name = 'ebay_apparel'

    start_urls = [



    def regex(self, data):

        if type(data) == list:

            return [re.sub('\s+', ' ', x).strip() for x in data]

        elif type(data) == str:

            return re.sub('\s+', ' ', data).strip()


            raise ValueError('Data type must be list or string')

    def parse(self, response):

        li_tags = response.css('ul.srp-results').css('li.s-item')

        for li in li_tags:

            product_url = li.css('a.s-item__link').xpath('@href').get()

            if product_url:

                yield response.follow(




    def parse_product_page(self, response):

        result_data = {}

        result_data['name'] = self.regex(



        result_data['price'] = self.regex(



        product_detail_table = response.css('div.itemAttr').css('table')

        header = product_detail_table.css(


        header = self.regex(header)

        values = product_detail_table.xpath('//td[@width="50.0%"]')

        result_values = []

        for val in values:

            text = ' '.join(val.xpath('.//text()').getall())


        result_data.update(dict(zip(header, result_values)))

        yield result_data
We scrutinized unstructured data and delivered insightful structured data that helped the client to understand where to focus and improve.

Web Scraping Data Sheet | Mindbowser

Why Mindbowser For Web Scraping?

When you appoint data scraping experts from Mindbowser, we dedicatedly provide end-to-end support to accomplish your organizational objectives quickly.

Mindbowser has been delivering high-quality web scraping services to all sizes of businesses across the world for more than 10 years. At Mindbowser, you will receive comprehensive support from our web data scraping experts, who have immense knowledge of the latest website scraping tools, technologies, and methodologies.

Mindbowser For Web Scraping



As the Internet has grown astronomically, and businesses have become progressively dependent on data, now it’s a compulsion to have data on every aspect of your business.

The advantages of web scraping and its processes have become an essential aspect of all decision-making processes for all-size businesses. It is clear that web scraping software tools will race ahead, and will give users a competitive advantage.

So start using web scraping according to your business needs, and it can help you achieve your desired business goal in a minimum time frame.

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